GUIDELINES
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- Authors are invited to submit their original manuscripts written in English via the online submission platform of Easychair (EasyChair).
- Each manuscript should include the complete paper text, all illustrations, and references. The manuscript should conform to the IEEE format. Authors are recommended to format their papers based on one of these templates: Suggested IEEE Proceedings Paper Template
- All papers must be in PDF format only, with savable text.
- Each paper must be no more than six pages (including the abstract, figures, tables, and references), double-columned, 10pt font.
- Accepted papers are allowed six pages in the conference proceedings free of charge. Each additional page beyond six pages is subject to the page charge of 150.00 EUR per page up to the eight-page limit.
- IMPORTANT: Your submission must not include information that serves to identify the authors of the manuscript, such as name(s) or affiliation(s) of the author(s), anywhere in the manuscript, abstract, or in the embedded PDF data. References and bibliographic citations to the author(s) own published works or affiliations should be made in the third person.
- By submitting a manuscript to IEEE COINS, the authors guarantee that the manuscript has not been previously published or accepted for publication in a substantially similar form in any conference, journal, or workshop. The only exceptions are i) workshops without archived proceedings, such as in the ACM/IEEE digital library (or where the authors chose not to have their paper appear in the archived proceedings), or ii) venues, such as IEEE CAL, where there is an explicit policy that such publication does not preclude longer conference submissions. These are not considered prior publications. Technical reports and papers posted on public social media sites, Web pages, or online repositories, such as arxiv.org, are not considered prior publications either. The authors also guarantee that no paper that contains significant overlap with the contributions of the submitted paper will be under review for any other conference, journal, or workshop during the COINS review period. Violation of any of these conditions will lead to rejection. As always, if you are in doubt, it is best to contact the program chair(s).
- We also note that the IEEE Plagiarism Policy (http://www.ieee.org/
publications/policies/ plagiarism_policy) covers a range of ethical issues concerning the misrepresentation of other works or one’s own work. - Paper Evaluation: All regular papers go through a blind peer-review process. Submitted manuscripts are carefully reviewed by several reviewers and rated considering Relevance, Originality, Technical Quality, Significance, and Presentation. Based on the corresponding score/comments given by reviewers, program and track chairs will decide if a paper can be accepted as a full regular paper (with 20+5 minutes of oral presentation) or as a short paper (with 13+2 minutes of oral presentation).
- It is crucial to adhere to the specified formatting guidelines (e.g., anonymous submission, page limits, font sizes, margins, and citation styles, among other requirements). Failure to comply with these guidelines will result in the rejection of the paper, regardless of its technical novelty or content.
- IMPORTANT: Final camera-ready versions must be identical to the submitted papers with the following exceptions; inclusion of author names/affiliation, correction of identified errors, and addressing reviewer-demanded changes. No other modifications of any kind are allowed, including modification of the title, change of the author list, reformatting, restyling, rephrasing, removing figures/results/text, etc. The TPC Chairs reserve the right to finally reject any manuscripts not adhering to these rules. A report detailing all the revisions made must be submitted together with the final camera-ready manuscript once any revision is conducted. The addition/removal of authors once the paper is accepted will have to be approved by the program chair since it potentially undermines the goal of eliminating conflicts for reviewer assignment.
- IEEE will hold the copyright for COINS proceedings. Authors of accepted papers must sign an IEEE copyright release form for their paper.
- IEEE’s Publishing Policy can be found here, and the Author Rights page can be found here. Any issues/questions authors have regarding the copyright form or IEEE Policy may be addressed to IEEE.
- An author of each accepted submission is required to:
- Produce a paper for the official conference proceedings.
- Make sure the final manuscript to be published passes the IEEE eXpress compliance check.
- Sign and submit a copyright form.
- Every accepted paper MUST have at least one author registered to the Conference by the time the camera-ready paper is submitted; at least one of the authors is also expected to attend the conference and present the paper. IEEE reserves the right to exclude a paper from distribution after the conference (e.g., removal from IEEE Xplore) if the paper is not presented at the conference.
- Note that following IEEE’s policy on authorship, anyone listed as Author on a paper must meet all the following criteria:
- They have made substantial intellectual contributions to some components of the original work described in the paper; and
- They have participated in drafting and/or revision of the paper; and
- They are aware that the paper has been submitted for publication; and
- They agree to be held accountable for any issues relating to the correctness or integrity of the work
SCIENTIFIC PAPERS
Complete manuscripts may be up to six pages in a standard IEEE two-column format, with the option to include two additional pages for a fee of €150 per page, where the first six pages are free, for a maximum total of eight pages. Authors are required to clearly articulate the significance of their work, highlight novel contributions, and describe its current development status. The submission process follows a double-blind review policy, requiring authors to anonymize their manuscripts to ensure impartial evaluation. Manuscripts that exceed the page limit or fail to adhere to the submission guidelines, including the requirement for double-blind review, will be returned without review to maintain the integrity and fairness of the evaluation process. Scientific papers can be submitted to the following tracks:
Track: Artificial Intelligence of Things (AIoT): From Edge to Cloud
This track explores advancements in the Artificial Intelligence of Things (AIoT), combining the power of AI with IoT systems to enable intelligent, scalable, and efficient solutions from device-level processing to large-scale cloud ecosystems. It emphasizes innovations in intelligent IoT devices, edge/fog computing, AI-powered communication protocols, and real-world deployment scenarios. Contributions focusing on the integration of AI to enhance IoT systems and applications are particularly encouraged.
Key Topics:
AIoT Devices and Sensors
- Smart and intelligent devices: sensors, sensor systems, and AI-powered front-ends.
- Low-power AIoT devices, wearable technologies, and body sensor networks.
- Embedded systems with on-device AI processing for real-time intelligence.
- Optimization of data traffic, latencies, and intelligent signal processing.
- Advanced sensing and edge intelligence for smart environments.
AIoT Communication and Networking
- AI-powered communication protocols and optimization for AIoT (6LoWPAN, RPL, 6TiSCH, etc.).
- Intelligent routing and transport protocols for AIoT networks.
- Machine-to-machine (M2M) and device-to-device (D2D) communications enhanced by AI.
- Integration of AI in 5G, LPWA, and next-generation networks for AIoT.
- AI-driven self-organization and self-healing networks for AIoT.
- Federated learning and edge intelligence in AIoT communication systems.
- Traffic modeling and performance evaluation with AI-enhanced analytics.
AIoT Platforms, Applications, and Services
- Intelligent platforms and frameworks for AIoT application development.
- Cyber-physical systems enhanced with AI for smart decision-making.
- AI-driven data analytics, visualization, and storage across edge, fog, and cloud.
- Distributed AI models for edge intelligence in IoT systems.
- Collaborative AI-powered IoT applications for smart environments.
- Real-world AIoT deployment scenarios, testbeds, and large-scale pilot programs.
AIoT Deployment and Standardization
- AIoT deployment in agriculture, retail, smart cities, healthcare, and beyond.
- Experimental AIoT prototypes, field trials, and performance evaluations.
- Integration of AI and IoT in future internet architectures.
- Standardization, regulation, and ethical considerations for AI in IoT.
Track: Artificial Intelligence, Machine Learning, and Cognitive Computing
This track invites groundbreaking contributions in artificial intelligence, machine learning, and cognitive computing. It explores cutting-edge methodologies, transformative applications, and emerging technologies like foundation models and generative AI.
Key Topics:
- Foundation models and large-scale pretrained architectures.
- Generative AI, including large language models (LLMs) and vision-language models (VLMs).
- Advanced neural architectures: CNNs, RNNs, GANs, transformers, and diffusion models.
- Neural generative models, autoencoders, and spiking neural networks (SNNs).
- Adaptive systems and brain-inspired representations.
- Multi-modal integration across vision, language, and other modalities.
- Transfer learning, ensemble methods, and reinforcement learning.
- Bayesian learning, Monte Carlo simulations, and Markov models.
- Few-shot, low-shot, semi-supervised, and unsupervised learning.
- Time-series analysis and predictive analytics.
- Federated learning and decentralized AI frameworks.
- Robust learning: adversarial training, explainability, and ethical AI.
- 3D vision, motion tracking, and scene understanding.
- Object detection, segmentation, and image/video analytics.
- Behavior recognition and logical representation in vision systems.
- Automatic speech recognition (ASR) and spoken language understanding.
- Speech-to-text, text-to-speech, and multilingual language processing.
- Spoken dialog systems, robust speech recognition, and spontaneous speech processing.
- Data mining across text, streams, processes, and networks.
- Business intelligence solutions using AI-driven insights.
- Vision-language integration for tasks like captioning and question answering.
- Trustworthy and explainable AI in high-stakes applications.
- Ethical AI and privacy-preserving techniques in AI models.
Track: Generative AI: Systems, Architectures, and Applications
This track explores the advancements and applications of Generative Artificial Intelligence (GenAI) across systems, architectures, and various disciplines. It emphasizes innovations in algorithm optimization, scalable system design, and transformative applications leveraging technologies like large language models (LLMs), vision-language models (VLMs), generative adversarial networks (GANs), and diffusion models. Submissions focusing on efficiency, hardware compatibility, and the integration of GenAI into real-world systems are highly encouraged.
Key Topics:
- Algorithm Optimizations for GenAI Deployment:
Techniques for optimizing algorithms for hardware compatibility, creating low-complexity, hardware-friendly models, and enabling scalable deployment across diverse applications such as image generation, language translation, and genomic research. - Circuits and Systems for GenAI Implementation:
System and circuit design for efficient GenAI implementation, including architecture design, ASIC/FPGA circuit optimization, and embedded software implementation on multi-core CPUs, GPUs, and DSPs. Topics also include addressing challenges in architecture security, performance evaluation, scalability, and energy efficiency. - Generative AI for Accelerating Circuit and System Design:
Applications of GenAI in design automation, efficient verification, and optimization of circuits and systems, leveraging tools such as LLMs for ASIC/FPGA design, synthesis, and validation workflows. - Applications of Generative AI Across Disciplines:
- Healthcare and Medicine: AI-driven drug discovery, medical image enhancement, mental health diagnostics, and genomics-based personalized medicine.
- Natural Language Processing (NLP): Advanced language models for text generation, multilingual summarization, and sentiment analysis.
- Engineering and Manufacturing: AI for generative design, robotics-enabled problem-solving, and optimization in product design and engineering workflows.
- Business and Finance: Applications in financial forecasting, market simulation, and AI-driven decision-making and customer service.
- Education and Training: AI-generated educational content, virtual tutoring systems, and immersive learning environments.
- Environmental Science: AI for predictive environmental modeling, climate change simulations, and sustainable practices.
- Gaming and Virtual Environments: Interactive content creation, generative storytelling, and AI-powered real-time enhancements in VR and AR.
- Security and Privacy: GenAI applications in cybersecurity, combating misinformation and deepfakes, and ensuring data privacy in AI-generated outputs.
Track: Hardware/Cyber Security and Privacy
This track addresses the critical challenges of safeguarding interconnected systems, focusing on robust hardware designs, secure communication architectures, and advanced privacy-preserving technologies. Researchers and practitioners are invited to submit their innovative solutions for mitigating evolving cyber threats and enhancing hardware resilience.
Key Topics:
- Hardware Security:
- Hardware-based attacks and countermeasures.
- Secure hardware design.
- Efficient and secure HW/SW implementations.
- Fault-resistant and tamper-detection designs.
- Secure Communication:
- Cryptographic protocols.
- Secure communication architectures.
- Network security.
- Emerging Technologies:
- IoT security.
- Blockchain and cybersecurity.
- Trustworthy AI.
- Machine learning-based security mechanisms.
- Satellite security.
- Cryptography:
- Lightweight cryptography.
- Postquantum cryptography.
- Applied Security:
- Security and privacy in healthcare.
- Security of critical infrastructure.
- Mobile security and privacy.
- Cyber Security:
- Threat models and attack strategies.
- Threat detection and mitigation.
- Intrusion and malware detection systems.
- Cybersecurity protocols and policies.
- Cross-layer security.
- Usable security.
- Privacy:
- Privacy and anonymization techniques.
- Privacy-enhancing technologies.
- Legal and ethical aspects of privacy.
Track: Distributed Ledger Technologies and Blockchain
This track explores advancements in blockchain and Distributed Ledger Technologies (DLTs), emphasizing their role in decentralized frameworks, IoT ecosystems, and innovative consensus mechanisms. Submissions are invited to present novel research, address real-world challenges, and propose performance optimizations in blockchain systems.
Key Topics:
- Recent developments in DLT and blockchain research.
- Theoretical advancements in DLT and blockchain for IoT.
- System design and implementation methods for blockchain-based IoT systems.
- Development of DLT-enabled IoT sensor networks.
- Decentralized security solutions for IoT using blockchain schemes.
- Threat models and attack strategies for blockchain and DLT in IoT.
- Decentralized keys, identity management, and access control mechanisms.
- Frameworks and software platforms for IoT security and privacy.
- Performance evaluation and experimental analysis of blockchain IoT schemes.
- Novel development and optimization of smart contracts in IoT ecosystems.
- Efficient consensus protocols and algorithms for DLTs in IoT devices.
- Integration of AI and machine learning with blockchain for IoT optimization.
- Convergence of AI, DLT, and blockchain for intelligent systems.
- Design of mathematical models and decentralized frameworks for DLT systems.
- Blockchain and DLT in peer-to-peer (P2P) and machine-to-machine (M2M) communications.
Track: Circuits and Systems (CAS) Designs for AI and AIoT
This track focuses on innovative circuit and system designs that support the demands of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT). It emphasizes creating energy-efficient, high-performance devices, scalable circuits, and integrated architectures to meet the computational and connectivity needs of modern intelligent systems. Contributions that address emerging technologies such as in-memory computing, silicon photonics, and neuromorphic engineering, as well as AI-focused accelerators and deep learning hardware, are particularly encouraged.
Key Topics:
- Emerging beyond-CMOS technologies for scalable AI and AIoT systems.
- Advanced sensory circuits and devices for AI-driven and AIoT applications.
- Silicon photonics for AI processing and high-speed communication.
- Robust device designs for low-power and high-variability environments.
- Spiking neural networks (SNNs) for neuromorphic computing and AI acceleration.
- In-memory computing (CiM) architectures for energy-efficient AI processing.
- Design and implementation of low-power AI accelerators for deep learning.
- Hardware optimization for neural networks, including deep learning and reinforcement learning.
- Communication circuits for high-speed, low-latency AI and AIoT systems.
- Circuits optimized for large-scale data processing and AI analytics.
- Hierarchical system designs supporting collaborative edge-cloud AI processing.
- Power modeling, optimization, and low-power circuit designs for AI systems.
- Cross-layer optimization strategies for scalable AI architectures.
- Neuromorphic engineering for biologically inspired AI systems.
- Advanced system-level solutions for distributed AI processing and decision-making.
Track: Communications and Networking for AIoT
This track explores advancements in communication technologies and networking paradigms to meet the growing demands of Artificial Intelligence of Things (AIoT) systems. It focuses on innovations in wireless communications, protocol design, and system-level optimizations, leveraging AI and machine learning to enhance connectivity, performance, and security. Submissions addressing theoretical breakthroughs, practical implementations, and real-world deployments are particularly encouraged.
Key Topics:
- Wireless communications, including cellular networks (4G, 5G, and beyond).
- Advanced communication theory and cognitive radios for intelligent systems.
- Signal processing techniques for AIoT communication.
- Novel communication protocols and cross-layer optimization for AIoT.
- Broadband wireless networks and software-defined wireless networks.
- Green communication technologies and energy-efficient networking.
- Terahertz communication for high-speed, low-latency applications.
- Ad hoc and sensor networks for distributed AIoT systems.
- Big data and data analytics in communication systems.
- AI and machine learning applications in communication networks.
- Federated learning and decentralized AI for communication systems.
- UAV networking and communication for AI-enabled applications.
- Vehicular communication technologies for autonomous and AI-driven systems.
- Spectrum sharing and interference management strategies.
- Cloud, edge, and fog computing integration with communication networks.
- Security, privacy, and attack detection in AIoT communication infrastructures.
- Case studies, testbeds, and deployment of AIoT communication systems.
Track: Low Power Design and Electronic Design Automation
This track explores innovative methodologies and tools for energy-efficient design and automation, addressing the needs of next-generation systems for Artificial Intelligence (AI) and Internet of Things (IoT) applications. The focus includes EDA for AI, advancing tools to optimize the design of AI-specific architectures and accelerating workflows for deep learning systems. Simultaneously, the track highlights automation techniques for low-power, scalable solutions across IoT and intelligent systems. Emerging approaches that integrate AI-driven EDA, Generative AI (GenAI), and Large Language Models (LLMs) into design workflows are particularly encouraged.
Key Topics:
- Optimization tools for designing deep learning accelerators and AI-specific architectures, including spiking neural networks (SNNs).
- System-level design, high-level synthesis, and power-aware optimization for AI and IoT.
- Generative AI (GenAI) and Large Language Models (LLMs) for automation in design workflows, including high-level synthesis (HLS), logic synthesis, place-and-route, security verification, test generation, and formal verification.
- LLM-aided system-level design methodologies and physical design processes.
- LLMs for reasoning, math, and optimization in the design process.
- LLM-aided verification, bug-fixing, and debugging in design automation workflows.
- Security and robustness of LLM-generated designs and workflows.
- Finetuning large foundation models for specialized EDA applications.
- New Datasets and Benchmarks for LLM-aided design
- AI-driven frameworks for simulation, testing, and formal verification of system designs.
- Specification and modeling languages for AI and intelligent systems.
- Design methodologies for machine learning hardware, including low-power AI accelerators and in-memory computing (CiM).
- CAD tools for optimizing cyber-physical systems, AI architectures, and IoT ecosystems.
- Power modeling, optimization, and low-power circuit design techniques for AI and IoT applications.
- Variability-aware and temperature-aware design methodologies for robust energy-efficient systems.
- Cross-layer optimization for integrated AI and IoT system architectures.
- Hierarchical design solutions for scalable AI processing.
- Emerging design technologies for future memories.
- Hardware-aware neural architecture search for efficient AI deployment.
- Neuromorphic engineering and biologically inspired design techniques for AI acceleration.
- Design methodologies, optimizations, verification, analysis and reliability for machine learning architectures.
- Approximate architectures for machine learning applications.
- Novel neural networks architectures and concepts for embedded computing.
- Co-design space exploration for ML applications.
Track: Robotics and Intelligent Systems
This track focuses on advancing the field of robotics by integrating intelligent systems that enable greater autonomy, adaptability, and interaction in dynamic environments. It emphasizes distributed robotics, human-robot collaboration, and AI-powered learning and control mechanisms, with applications spanning industries such as healthcare, manufacturing, and logistics. Contributions addressing innovations in robotics technologies, perception, learning, and real-world applications are highly encouraged.
Key Topics:
- Distributed Robotics: Multi-robot systems, fleet management, coordination, task and resource allocation, Internet of Robotic Things (IoRT), and cloud robotics.
- Perception: Distributed environment perception, multi-robot SLAM, and interactive perception techniques.
- Human-Robot Interaction: User interfaces, shared autonomy, human-robot teaming, remote interaction, telepresence, and teleoperation.
- Learning: Decentralized learning, multimodal learning, multi-agent systems, learning for perception, and robust learning methods.
- Planning and Control: Navigation and planning for fleets, shared control, exploration, distributed control, and efficient task and resource allocation.
- Applications: Robotics in industries such as manufacturing, logistics, maintenance, and inspection, as well as healthcare applications for service, manipulation, assistance, and monitoring.
Track: Digital Healthcare and Well-being
This track focuses on the intersection of automation technology, artificial intelligence, wearable computing, IoT, and healthcare to advance the field of digital healthcare and well-being. It emphasizes innovative solutions, devices, and frameworks for personalized health monitoring, medical diagnostics, and secure health data management. Submissions exploring the convergence of technology and healthcare are highly encouraged.
Key Topics:
- AIoT for medical and healthcare applications.
- Mobile and e-Health sensing systems.
- Wearable, outdoor, and home-based sensors for health monitoring.
- Generative AI (GenAI) applications in healthcare decision-making and diagnostics.
- Large Language Models (LLMs) for healthcare applications, including medical records analysis and conversational AI.
- Explainable AI (XAI) for transparent healthcare predictions and recommendations.
- Novel devices, circuits, and architectural support for e-health applications.
- Printable electronics and energy harvesting for healthcare systems.
- Nano-CMOS and Post-CMOS-based sensors, circuits, and controllers.
- AI-driven cloud-enabled body sensor networks and secure middleware for e-health.
- Energy-efficient PHY/MAC and networking protocols for e-health applications.
- Reprogrammable and reconfigurable embedded systems for healthcare.
- eHealth traffic characterization and scalable software architectures.
- Big data analytics, machine learning algorithms, and distributed healthcare analytics.
- Privacy-preserving and security approaches for large-scale health data analytics.
- Federated learning for secure and collaborative healthcare data processing.
- Fog and edge computing for resource allocation and real-time healthcare applications.
- Fault tolerance, reliability, and scalability for eHealth systems.
- AI-based early detection and prediction of diseases using multimodal data.
- Integration of AI and IoT in predictive health monitoring systems.
- Autonomic analysis, monitoring, and situation alertness in healthcare systems.
- Case studies in telemedicine, remote diagnostics, and smart health management architectures.
Track: Industry 4.0 and Smart Manufacturing
This track explores emerging technologies and strategies for the design and implementation of smart factories in the Industry 4.0 era. It emphasizes the integration of AIoT, robotics, AI, and advanced manufacturing techniques to improve productivity, flexibility, and sustainability in modern industries. Contributions addressing real-world implementations and innovative solutions are highly encouraged.
Key Topics:
- Intelligent IoT-based solutions for smart manufacturing.
- Innovative sensing strategies for process monitoring and tracking product history.
- Digital twins for product design and smart manufacturing.
- Smart interconnection and interoperation for digital twin ecosystems.
- Machine learning techniques for process control and quality improvement.
- Real-time IoT data analytics, data aggregation, and event detection.
- Integration of additive manufacturing technologies in smart factories.
- Smart modeling of factory floors and sensor-integrated manufacturing processes.
- Human-machine interfaces and communication technologies.
- Immersive technologies: augmented reality (AR), virtual reality (VR), and mixed reality (MR).
- Edge-fog-cloud computing for smart factory architectures.
- Privacy-preserving machine learning and secure data sharing in Industry 4.0.
- Applications of distributed ledger technologies (DLTs) and blockchain in smart manufacturing.
- Advanced robotics: collaborative and adaptive robotic systems.
- Semantic Web of Things for interconnected smart factory systems.
- Real-world case studies and Industry 4.0 implementation experiences.
Track: Smart Infrastructure
This track focuses on the integration of cutting-edge technologies such as AIoT, AI, edge-cloud computing, and distributed systems to develop intelligent, sustainable, and resilient infrastructure. It encompasses smart cities, agriculture, energy, mobility, and beyond, addressing both foundational technologies and their applications. Submissions are encouraged that highlight innovative solutions, deployment strategies, and cross-domain applications to redefine the future of infrastructure.
Key Topics:
Smart City and Urban Management
- AIoT-enabled urban infrastructure for real-time monitoring and control.
- AI and machine learning for urban planning, traffic management, and predictive maintenance.
- Edge-to-cloud computing for resource optimization in urban environments.
- Intelligent systems for public safety, disaster management, and resilience planning.
- Renewable energy and energy storage solutions integrated into urban environments.
- Advanced networking architectures for seamless 5G/6G-enabled smart city ecosystems.
- Urban environment analytics: pollution monitoring, waste management, and water systems.
Smart Agriculture and Rural Development
- Sensor networks and AIoT for precision farming, irrigation, and soil health monitoring.
- Drones and autonomous vehicles for crop monitoring, pest detection, and yield estimation.
- Big data analytics and AI for climate-resilient agriculture.
- Smart solutions for mixed farming systems, aquaculture, and forestry.
- Distributed platforms for resource sharing in rural farming communities.
- Energy-efficient IoT systems for remote and rural agricultural applications.
Smart Energy and Grid Systems
- AI-driven demand-response systems and renewable energy integration.
- Advanced metering infrastructure (AMI) for smart grids.
- Real-time data analytics and fault detection in energy distribution networks.
- Blockchain for secure transactive energy management and microgrid optimization.
- Energy storage systems, including battery management and grid-scale solutions.
- IoT and AI for smart energy systems in urban, rural, and industrial settings.
- Edge computing for real-time energy management and predictive maintenance.
Smart Mobility and Transportation
- Autonomous and connected vehicle technologies for safer, efficient transportation.
- Mobility-as-a-Service (MaaS) platforms integrating public and private transport systems.
- IoT and AI for traffic prediction, congestion reduction, and fleet optimization.
- Advanced hardware and software for autonomous aerial vehicles and drones.
- Cybersecurity and safety measures for intelligent transportation systems (ITS).
- Integrated multimodal transportation planning and management.
- Infrastructure for electric vehicles (EVs) and charging networks.
Smart Water and Waste Management
- AIoT solutions for water quality monitoring, distribution, and wastewater treatment.
- AI-driven predictive maintenance for water infrastructure systems.
- Smart waste collection and recycling systems leveraging AIoT and data analytics.
- Integrated water and waste management platforms for urban environments.
Cross-Domain Integration and Emerging Technologies
- Cyber-physical systems for integrated infrastructure solutions.
- Standardization frameworks and interoperability for multi-domain IoT systems.
- AI, Edge AI and federated learning for decentralized infrastructure optimization.
- Real-world deployment scenarios, testbeds, and field trials for smart infrastructure.
- Privacy, security, and data governance for large-scale infrastructure systems.
- Sustainable and resilient designs for climate change adaptation.
SPECIAL SESSIONS PROPOSALS
Special session proposals are invited on emerging and cutting-edge topics, panel discussions, or embedded tutorials. Each proposal must include a 150-200 word abstract, the names and affiliations of the organizers, and a list of at least three speakers, complete with their contact information and tentative presentation titles.
Accepted special session proposals will require organizers and speakers to prepare one of the following options for inclusion in the formal conference proceedings:
- (a) A single collaborative paper authored by all or a subset of the presenters, up to 10 pages (excluding references).
- (b) Three individual papers, each up to 6 pages (including references).
TUTORIALS PROPOSALS
IEEE COINS invites proposals for Tutorials. Tutorial sessions are designed to offer participants a comprehensive overview and discussion of advanced topics relevant to the conference. Tutorials aim to highlight innovative ideas, emerging trends, or breakthrough applications in various fields covered by the conference. Participants will have the opportunity to learn cutting-edge techniques, explore pioneering concepts, and gain insights from domain experts. Tutorials typically run for 1.5-2 hours, but longer half-day sessions (split into two blocks of 1.5-2 hours each) may also be considered.
WORKSHOPS AND TUTORIALS PROPOSALS
IEEE COINS invites proposals for Workshops. Workshops are half-day events that encourage active discussions on focused topics within specific fields of interest. These workshops typically include peer-reviewed papers, invited talks (optional, without paper submissions), and presentations. Workshops provide an engaging forum for researchers and practitioners to exchange ideas, foster collaborations, and address key challenges in their domains. Accepted papers from workshops will be included in the IEEE COINS Proceedings, which will be submitted to the IEEE Xplore Digital Library and other indexing services.
CALL FOR SPEAKERS & PANELS
Are you an executive, strategist, or professional working in the fields of IoT, Big Data, AI/ML, Blockchain, Cloud Computing, or Robotics? The purpose of the COINS Pavilion is to present content that is interesting to both the technical and business audiences that attend COINS. There are three options when submitting a proposal:
- Panels (45 minutes long). The topic of each panel should be interesting, timely, and relevant to multiple segments of COINS attendees. Controversy is appropriate and encouraged.
- Individual (Technical or Demo) oral presentations (20 minutes long) without any paper submission. If any presenters would also like to submit a technical research paper for publication, then that option is available, if desired. All submitted papers will be peer-reviewed for acceptance, and there is no guarantee that papers submitted by invited presenters will be accepted.
- Mini-Oral Talk (each 10-minute presentation | ideally C-level speakers).